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The goal of the project is to provide high level , general and aggregated approach to sentiment analysis of Yelp Users and Key behaviors. Hadoop was used to run Big Data. Data was uploaded to HDFS, Hive QL was used to extract the relevant data and further visualization was done using Tableau.

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prati-y/CIS-5200-Yelp-Data-Analysis-Using-Hive

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Yelp-Data-Analysis-Using-Hive

Description Problem Statement

Provide a high-level, general, and aggregated approach to sentiment analysis. Visualize the results to find insights. Overall sentiment of yelp users (yelpers) and behaviors Healthcare and Food/Beverage category. What insights can we obtain for the US healthcare system? What does the data show towards food establishments across the country?

Project Workflow:

Ingested the data to the Hadoop File System (Hdfs)

Hive Table Creation (Hive Processing)

Performed Data Cleaning Using HiveQL

Followed ETL process using HiveQL

Performed the Data Analysis to interpret the findings

Created data visualizations using Excel Power Map and Tableau.

Team Members : Philip Wong, Pratiksha Yadav, Pooja Madhup, Shailja Pandit

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The goal of the project is to provide high level , general and aggregated approach to sentiment analysis of Yelp Users and Key behaviors. Hadoop was used to run Big Data. Data was uploaded to HDFS, Hive QL was used to extract the relevant data and further visualization was done using Tableau.

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